36,299 research outputs found
Memory vectors for similarity search in high-dimensional spaces
We study an indexing architecture to store and search in a database of
high-dimensional vectors from the perspective of statistical signal processing
and decision theory. This architecture is composed of several memory units,
each of which summarizes a fraction of the database by a single representative
vector. The potential similarity of the query to one of the vectors stored in
the memory unit is gauged by a simple correlation with the memory unit's
representative vector. This representative optimizes the test of the following
hypothesis: the query is independent from any vector in the memory unit vs. the
query is a simple perturbation of one of the stored vectors.
Compared to exhaustive search, our approach finds the most similar database
vectors significantly faster without a noticeable reduction in search quality.
Interestingly, the reduction of complexity is provably better in
high-dimensional spaces. We empirically demonstrate its practical interest in a
large-scale image search scenario with off-the-shelf state-of-the-art
descriptors.Comment: Accepted to IEEE Transactions on Big Dat
Hashmod: A Hashing Method for Scalable 3D Object Detection
We present a scalable method for detecting objects and estimating their 3D
poses in RGB-D data. To this end, we rely on an efficient representation of
object views and employ hashing techniques to match these views against the
input frame in a scalable way. While a similar approach already exists for 2D
detection, we show how to extend it to estimate the 3D pose of the detected
objects. In particular, we explore different hashing strategies and identify
the one which is more suitable to our problem. We show empirically that the
complexity of our method is sublinear with the number of objects and we enable
detection and pose estimation of many 3D objects with high accuracy while
outperforming the state-of-the-art in terms of runtime.Comment: BMVC 201
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